A researcher wanted to develop a model to predict how long individuals will live. After consulting a number of physicians, she collected data for the age at death (y), the average number of hours of exercise per week (x]), the cholesterol level (x2), and the number of points by which the individual's blood pressure exceeded the recommended value (x3). A random sample of 40 individuals was selected. The estimation results of the multiple regression model are shown below: Explanatory variables Coefficients Standard Errors Intercept 55.8 11.8 X1 1.79 0.44 X2 -0.021 0.011 X3 -0.016 0.014 Number of Observation, N = 40 Sum of Squared Residuals, SSR = 3220 Total Sum of Square, SST = 4166 (a) Write down the Sample Regression Function (SRF) in an equation form and interpret each of the estimated slope coefficients